private List <MatchResult> MatchEntitiesWithIndicesPostTokenizeApproach(ProcessedDataset processedDataset, List <string> dataset, string inputSentence, float threshold, int ngramSize = 3)
{
// initial match (reduce database)
var initialMatchResult = MatchEntitiesWithoutIndices(processedDataset, dataset, inputSentence, ngramSize);
if (initialMatchResult.Count == 0)
{
return(initialMatchResult);
}
// get initial match sentences TFIDF values
var matchingSentencesIndices = initialMatchResult.Select(m => m.DatabaseMatchInfo.MatchIndex).ToList();
var initialMatchTFIDFMatrix = processedDataset.TFIDFMatrix.Where((rowValue, rowIndex) => matchingSentencesIndices.Contains(rowIndex)).ToArray();
var initialMatchTFIDFAbsoluteValues = processedDataset.TFIDFMatrixAbsoluteValues.Where((rowValue, rowIndex) => matchingSentencesIndices.Contains(rowIndex)).ToArray();
var initialMatchAsDataset = dataset.Where((rowValue, rowIndex) => matchingSentencesIndices.Contains(rowIndex)).ToList();
// get all possible tokens of input sentence
var sentenceTokens = StringTokenizer.GetAllPossibleTokens(inputSentence, processedDataset.MaximumWordCount, ngramSize);
var inputTokensTFIDFMatrix = TFIDFController.CalculateInputSenenteceTokensTFIDFMatrix(sentenceTokens, processedDataset, ngramSize);
// re-matching (with resolution)
var similarityValuesMatrix = DotProductCalculator.GetDotProduct(inputTokensTFIDFMatrix, initialMatchTFIDFMatrix, matrix2Abs: initialMatchTFIDFAbsoluteValues);
// re-filter
var tfidfThreshold = 0.5f;
var tfidfMatches = MatchFilter.FilterByThresholdBatch(similarityValuesMatrix, initialMatchAsDataset, sentenceTokens, tfidfThreshold);
//post processing
var updatedScoresMatches = PostprocessingController.UpdateMatchScores(tfidfMatches);
return(MatchFilter.FilterByThreshold(updatedScoresMatches, threshold));
}
private List <MatchResult> MatchEntitiesWithoutIndices(ProcessedDataset processedDataset, List <string> dataset, string inputSentence, int ngramSize)
{
// calculate input sentence TFIDF vector
var inputSentenceTFIDFVector = TFIDFController.CalculateInputSentenceTFIDFVector(inputSentence, processedDataset, ngramSize);
// calculate cosine similarity
var cosineSimilarityValues = DotProductCalculator.GetDotProduct(inputSentenceTFIDFVector, processedDataset.TFIDFMatrix, matrixAbs: processedDataset.TFIDFMatrixAbsoluteValues);
// filter result
var tfidfThreshold = 0.4f;
return(MatchFilter.FilterByThreshold(cosineSimilarityValues, dataset, tfidfThreshold));
}
private List <MatchResult> MatchEntitiesWithIndicesPreTokenizeApproach(ProcessedDataset processedDataset, List <string> dataset, string inputSentence, float threshold, int ngramSize = 3)
{
// get all input sentence possible tokens
var sentenceTokens = StringTokenizer.GetAllPossibleTokens(inputSentence, processedDataset.MaximumWordCount, ngramSize);
// calculate tokens TFIDF matrix
var inputTokensTFIDFMatrix = TFIDFController.CalculateInputSenenteceTokensTFIDFMatrix(sentenceTokens, processedDataset, ngramSize);
// calculate tokens cosine similarity
var similarityValuesMatrix = DotProductCalculator.GetDotProduct(inputTokensTFIDFMatrix, processedDataset.TFIDFMatrix, matrix2Abs: processedDataset.TFIDFMatrixAbsoluteValues);
// filter results
var tfidfThreshold = 0.5f;
var tfidfMatches = MatchFilter.FilterByThresholdBatch(similarityValuesMatrix, dataset, sentenceTokens, tfidfThreshold);
// post processing
var updatedScoresMatches = PostprocessingController.UpdateMatchScores(tfidfMatches);
return(MatchFilter.FilterByThreshold(updatedScoresMatches, threshold));
}